Federated learning and privacy-preserving AI
3 European H2020 organizations list this as part of their work — 1 as their primary capability.
Most active in this area
- NVIDIA SWITZERLAND AG
Global GPU computing leader providing high-performance computing infrastructure, parallel programming expertise, and AI acceleration to European research consortia.
“MELLODDY applied federated learning with privacy by design for multi-party drug discovery without sharing raw data.”
CH3 projects - THRIDIUM LIMITED
London AI and VR technology SME delivering medical imaging AI systems and serious games training simulations in large EU research consortia.
“INCISIVE involved federated learning, data donation frameworks, and blockchain for health data governance, indicating hands-on technical depth in privacy-sensitive AI infrastructure.”
PrimarySMEUK2 projects - WEB-IQ BV
Dutch AI SME specializing in NLP, computer vision, and federated learning for law enforcement detection of illegal online content and cyberthreats.
“Federated learning was a named keyword in GRACE, indicating Web-IQ has hands-on experience enabling AI model training across distributed, sensitive datasets without centralizing raw data.”
SMENL2 projects